EAGER: AI-Native Cooperative Perception Networking via Joint Radar-Communication Vehicular — NSF Award to University of Texas at D
Modern vehicles increasingly rely on millimeter-wave (mmWave) radar sensors to support driver-assistance and automated-driving capabilities. However, each vehicle still perceives the world only from its own vantage point. Buildings, large trucks, adverse weather, clutter, and simple distance limits can therefore hide c
| Award title | EAGER: AI-Native Cooperative Perception Networking via Joint Radar-Communication Vehicular |
|---|---|
| Award ID | 2625164 |
| Awardee | University of Texas at Dallas |
| City | RICHARDSON |
| State | TX |
| Amount obligated | $299,741 |
| Principal investigator | Murat Torlak |
| Program | Networking Technology and Syst |
| Start date | 07/01/2026 |
| Abstract | Modern vehicles increasingly rely on millimeter-wave (mmWave) radar sensors to support driver-assistance and automated-driving capabilities. However, each vehicle still perceives the world only from its own vantage point. Buildings, large trucks, adverse weather, clutter, and simple distance limits can therefore hide critical hazards, such as a pedestrian entering a crosswalk, a vehicle approaching a blind intersection, or a fast-sudden lane merging conflict. While connected-vehicle technologies |
| Source | NSF Awards |
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